A Region Thesaurus Approach for High-Level Concept Detection in the Natural Disaster Domain
A Region Thesaurus Approach for High-Level Concept Detection in the Natural Disaster Domain
复制标题
自然灾害领域高级概念检测的区域词库方法
DOI：
10.1007/978-3-540-77051-0_7
复制
发表时间：
2007
影响因子：
4.8
通讯作者：
Yannis Avrithis
中科院分区：
文献类型：
--
作者：
E. Spyrou;Yannis Avrithis
提出了一种基于区域词库的高层次特征检测方法。MPEG-7特征是从分割的区域和一个大的图像集局部提取的。应用层次聚类方法，并选择相对较少的区域类型。这组区域类型定义了区域同义词库。使用这个词库，低级别的功能映射到高级别的概念作为模型向量。然后使用该表示来训练基于支持向量机的特征检测器。作为下一步，潜在语义分析应用于模型向量，以进一步提高分析性能。发现的高级概念来自自然灾害领域。
This paper presents an approach on high-level feature detection using a region thesaurus. MPEG-7 features are locally extracted from segmented regions and for a large set of images. A hierarchical clustering approach is applied and a relatively small number of region types is selected. This set of region types defines the region thesaurus. Using this thesaurus, low-level features are mapped to high-level concepts as model vectors. This representation is then used to train support vector machine-based feature detectors. As a next step, latent semantic analysis is applied on the model vectors, to further improve the analysis performance. High-level concepts detected derive from the natural disaster domain.